Run nested cross-validation experiment on the CTRP drug sensitivity dataset, with
the Gaussian + Gaussian (multivariate posterior) + Exponential model.
'''
import sys, os
project_location = os.path.dirname(__file__)+"/../../../../"
sys.path.append(project_location)
from BMF_Priors.code.models.bmf_gaussian_gaussian_exponential import BMF_Gaussian_Gaussian_Exponential
from BMF_Priors.code.cross_validation.nested_matrix_cross_validation import MatrixNestedCrossValidation
from BMF_Priors.data.drug_sensitivity.load_data import load_ctrp_ec50_integer
''' Settings BMF model. '''
method = BMF_Gaussian_Gaussian_Exponential
R, M = load_ctrp_ec50_integer()
hyperparameters = { 'alpha':1., 'beta':1., 'lamb':0.1 }
train_config = {
'iterations' : 200,
'init' : 'random',
}
predict_config = {
'burn_in' : 180,
'thinning' : 1,
}
''' Settings nested cross-validation. '''
K_range = [3,4,5,6,7]
no_folds = 5
no_threads = 5
'''
Run nested cross-validation experiment on the CTRP drug sensitivity dataset, with
Poisson likelihood, Gamma priors, and Gamma hierarchical priors.
'''
project_location = "/Users/thomasbrouwer/Documents/Projects/libraries/"
import sys
sys.path.append(project_location)
from BMF_Priors.code.models.bmf_poisson_gamma_gamma import BMF_Poisson_Gamma_Gamma
from BMF_Priors.code.cross_validation.nested_matrix_cross_validation import MatrixNestedCrossValidation
from BMF_Priors.data.drug_sensitivity.load_data import load_ctrp_ec50_integer
''' Settings BMF model. '''
method = BMF_Poisson_Gamma_Gamma
R, M = load_ctrp_ec50_integer()
hyperparameters = {'a': 1., 'ap': 1., 'bp': 1.}
train_config = {
'iterations': 200,
'init': 'random',
}
predict_config = {
'burn_in': 180,
'thinning': 1,
}
''' Settings nested cross-validation. '''
K_range = [1, 2, 3]
no_folds = 5
no_threads = 5
parallel = False
folder_results = './results/poisson_gamma_gamma/'
output_file = folder_results + 'results.txt'
